Body mass index (BMI) is the most widely used measure to diagnose obesity. However, the diagnostic accuracy of BMI to detect excess in body adiposity is largely unknown.
A cross-sectional design of 13,601 subjects (age 20–79.9 years; 48% men) from the Third National Health and Nutrition Examination Survey. Bioelectrical impedance analysis was used to estimate body fat percent (BF %). We assessed the diagnostic performance of BMI using the World Health Organization reference standard for obesity of BF % > 25% in men and > 35% in women. We tested the correlation between BMI and both, BF % and lean mass by sex and age groups.
BMI-defined obesity (≥ 30 kg/m2) was present in 21% of men and 31% of women, while BF %-defined obesity was present in 50% and 62%, respectively. A BMI ≥ 30 had a high specificity (95% in men and 99% in women), but a poor sensitivity (36% and 49 %, respectively) to detect BF %-defined obesity. The diagnostic performance of BMI diminished as age increased. BMI had a good correlation with BF % in men (R2 = 0.44) and women (R2 = 0.71), but also with lean mass (R2 = 0.50 and 0.55, respectively).
Despite the good correlation between BMI and BF %, the diagnostic accuracy of BMI to diagnose obesity is limited, particularly for individuals in the intermediate BMI ranges. A BMI cut-off of ≥ 30 kg/m2 has a good specificity but misses more than half of people with excess fat. These results help to explain the U and J-shape association between BMI and outcomes.
Could this have something to do with the recent “revelation” that obesity is not generally bad for health? I think so. BMI-defined obesity missed many of the BF-defined obese. In other words, many of those with lower BMIs are actually obese, thus their health is statistically the same as the BMI-defined obese.